op {
  graph_op_name: "RandomDataset"
  visibility: HIDDEN
  in_arg {
    name: "seed"
    description: <<END
A scalar seed for the random number generator. If either seed or
seed2 is set to be non-zero, the random number generator is seeded
by the given seed.  Otherwise, a random seed is used.
END
  }
  in_arg {
    name: "seed2"
    description: <<END
A second scalar seed to avoid seed collision.
END
  }
  summary: "Creates a Dataset that returns pseudorandom numbers."
  description: <<END
Creates a Dataset that returns a stream of uniformly distributed
pseudorandom 64-bit signed integers.

In the TensorFlow Python API, you can instantiate this dataset via the
class `tf.data.experimental.RandomDataset`.

Instances of this dataset are also created as a result of the
`hoist_random_uniform` static optimization. Whether this optimization is
performed is determined by the `experimental_optimization.hoist_random_uniform`
option of `tf.data.Options`.
END
}
